How to use Python's asyncio common functions?
Definition of coroutine
Need to use async def statement
What coroutine can do:
1. Wait for a future result
2 , wait for another coroutine (produce a result or raise an exception)
3. Produce a result to the coroutine that is waiting for it
4. Throw an exception to the coroutine that is waiting for it Program
Running of the coroutine
Call the coroutine function, the coroutine will not start running, it just returns a coroutine object
There are two ways to run the coroutine object Method:
1. Use await
to wait for it in another already running coroutine
2. Plan its execution through the ensure_future
function
Only when the loop of a certain thread is running, the coroutine can run
The following example:
First get the default loop of the current thread, and then transfer the coroutine object Handed to loop.run_until_complete, the coroutine object will then be run in the loop
loop = asyncio.get_event_loop() loop.run_until_complete(do_some_work(3))
run_until_complete
is a blocking call, and it will not return until the coroutine is finished running
The parameter is a future, but what we pass to it is a coroutine object. It does an internal check and wraps the coroutine object into a future through the ensure_future function
We can write like this:
loop.run_until_complete(asyncio.ensure_future(do_some_work(3)))
Multiple coroutines running
Multiple coroutines run in a loop. In order to hand over multiple coroutines to the loop, you need to use the asyncio.gathre
function
loop.run_until_complete(asyncio.gather(do_some_work(1), do_some_work(3)))
Or store the coroutine object in the list first, which is more common.
loop = asyncio.get_event_loop() #获取当前线程loop coros_list = [] for i in range(2000): coros_list.append(main(i)) loop.run_until_complete(asyncio.gather(*coros_list))
gather plays the role of aggregation, packaging multiple futures into a single future, because loop.run_until_complete only accepts a single future.
About loop.close()
Simply speaking, as long as the loop is not closed, it can still run. :
loop = asyncio.get_event_loop() #获取当前线程loop loop.run_until_complete(do_some_work(loop, 1)) loop.run_until_complete(do_some_work(loop, 3)) loop.close()
But if it is closed, it can no longer run:
loop = asyncio.get_event_loop() #获取当前线程loop loop.run_until_complete(do_some_work(loop, 1)) loop.close() loop.run_until_complete(do_some_work(loop, 3)) # 此处异常
Callback
Joining the coroutine is an IO read operation. After he finishes reading the data, We would like to be notified for further processing of the data. This can be achieved by adding callbacks to the future
def done_callback(futu): print('Done') futu = asyncio.ensure_future(do_some_work(3)) futu.add_done_callback(done_callback) loop.run_until_complete(futu)
Event loop
The event loop will run asynchronous tasks and callbacks, perform network IO operations, and run child processes
From asyncio event loop In the policy document, we learned that event loop policy is a process global object that controls the management of all event loops in the process.
The global policy of the process defines the meaning of the context controlled by the policy, and manages separate event loops in each context. The context defined by the default policy is the current thread, which means that different threads are Different contexts, therefore different event loops.
Get the event loop
asyncio.get_running_loop() # 返回当前os线程中正在运行的事件循环 asyncio.get_event_loop() # 获取当前事件循环 asyncio.set_event_loop(loop) # 获取当前事件循环 asyncio.new_event_loop() # 创建并返回一个新的事件循环对象
asyncio.get_event_loop()
If:
The current thread is Main thread
The current thread has not started event loop
Calling the asyncio.get_event_loop() method will generate a new default event loop and set it For the current thread's event loop.
At this time, get_event_loop() is equivalent to:
loop = asyncio.new_event_loop() asyncio.set_event_loop(loop)
The above is the detailed content of How to use Python's asyncio common functions?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

To run Python code in Sublime Text, you need to install the Python plug-in first, then create a .py file and write the code, and finally press Ctrl B to run the code, and the output will be displayed in the console.

VS Code can run on Windows 8, but the experience may not be great. First make sure the system has been updated to the latest patch, then download the VS Code installation package that matches the system architecture and install it as prompted. After installation, be aware that some extensions may be incompatible with Windows 8 and need to look for alternative extensions or use newer Windows systems in a virtual machine. Install the necessary extensions to check whether they work properly. Although VS Code is feasible on Windows 8, it is recommended to upgrade to a newer Windows system for a better development experience and security.

Writing code in Visual Studio Code (VSCode) is simple and easy to use. Just install VSCode, create a project, select a language, create a file, write code, save and run it. The advantages of VSCode include cross-platform, free and open source, powerful features, rich extensions, and lightweight and fast.

VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.
